OBJECTIVE: To estimate disability rates and explore associations, identifying
the most significant socioeconomic markers associated with the prevalence of
mobility disability among elderly women.METHODS: National mobility disability rates were estimated based on information
from the 1998 National Household Survey (PNAD), conducted by the Instituto
Brasileiro de Geografia e Estatística. The present study analyzes
the elderly women population, totaling 16,186 subjects. Logistic regression
models were constructed considering "difficulty walking 100 meters" as the dependent
variable.RESULTS: The prevalence of markers of mild, moderate and severe disability
was greater among women, and increased with age. In logistic regression analysis,
markers most strongly associated with increased prevalence of mobility disability
were age, gender, low schooling, and low income. Rural residence was also associated
with reduced prevalence.CONCLUSIONS: Our results suggest potential risk factors for the development
of functional decline in elderly women, given that the associations encountered
were consistent with those reported by other studies in the literature.

The study of disability among elderly subjects is important if we are to understand
how people live the additional years of life gained with increased longevity.
This is a worldwide phenomenon, but, in countries where the aging process is
not recent, there is greater knowledge of the patterns of disability among the
elderly. In Brazil, there are few studies addressing this subject on a national
basis.9,12 It is hence opportune to study this phenomenon based on
the results of the 1998 National Household Survey (Pesquisa Nacional por
Amostragem de Domicílios  PNAD),8 and, more specifically,
the results of its Health Supplement. Disability is defined as the difficulty  due to impairment  in performing typical activities or activities desired
by society.19 It is to a greater extent an indicator of the consequences
of a disease process than a measure of impairment or of specific morbidity.18
It is becoming a particularly useful concept for the evaluation of the health
status of elderly persons, who often show several diseases simultaneously, with
different degrees of severity and different impact on day-to-day life.

According to the Brazilian Institute for Geography and
Statistics (Instituto Brasileiro de Geografia e
Estatística  IBGE),8 population
projections in Brazil show a trend towards an increase in the
number of elderly persons, which should exceed 25 million in
2020, with a predominance of women (about 15 million). In studies
of the prevalence of functional disability, rates are higher
among women than among men, although these results are more
likely to reflect differences in survival time with limitations.
Studies carried out in the United States and Great Britain show
that women do not develop functional disability with greater
frequency than men, but they survive for longer than men do with
these limitations.1,6,11

This may be explained, at least partly, by differences in the
diseases associated with the men and women who report
disabilities.6 Interventions potentially capable of
reducing the burden of functional disability among the elderly
are being explored with the goal of developing novel prevention
and treatment strategies capable of diminishing the functional
consequences of chronic diseases among the elderly population,
and more specifically among elderly women, who live to older
ages.16

In
a metanalysis of studies carried out mainly in the United States,
Stuck et al17 reported smoking, increase and reduction
of body mass index, lack of (as well as excessive) alcohol
consumption when compared to moderate consumption, low frequency
of social contact, and depression as important causes of future
limitations. In addition to these individual factors, a strong
association is reported between socioeconomic status and
limitations in elderly persons in both longitudinal and
cross-sectional studies in the United States and
Europe.3,4,10,13

The aim of the present study is to estimate the rates of
mobility disability among women aged 60 years and older and to
identify sociodemographic factors associated with the prevalence
of mobility disability.

METHODS

The present study was carried out based on data from the
PNAD,8 which is representative of the total population
living in Brazil in September 1998 (excluding the rural area of
the North Region). In the 112,434 households sampled by the PNAD,
28,943 persons aged 60 years and older were found and were
included in the sample. Of these, 16,186 were women and 12,757
were men. Whenever possible, all members of the household were
interviewed; persons living in collective residences were
included in the sample, but accounted for only 0.1% of the total
elderly population. Of the 28,943 subjects in our sample, we
excluded from the analysis the subjects with values missing for
the following fields: 'color' (2), 'schooling' (14), 'family
income' (1,161), 'home ownership' (35), 'goods ownership' (35),
'sanitary conditions of the residence' (33). In the present
analysis, we will consider only the data on women.

Functional disability is frequently evaluated based on
self-reporting or on the need for help to perform basic personal
care activities (activities of daily living  ADL) as well as
more complex activities necessary for living independently in the
community (instrumental activities of daily living  IADL).

The ADL evaluates the severest degree of limitation in the
functional spectrum, and elderly persons may show great
functional decline without showing limitations in these
activities. This indicator is therefore of limited use in the
identification of changes with time and in the measurement of the
impact of interventions. IADL are considered as more complex than
personal care activities, and include shopping, cooking, domestic
chores, laundry, commuting, taking medication, handling money,
and using a telephone.

In
addition to ADL and IADL, a wide variety of other measures of
self-reported functional status have been developed. The
evaluation of mobility has been considered as an important
component of functional evaluation. Mobility can be evaluated by
self-report, using a hierarchical approach beginning with simple
mobility tasks, such as moving from the bed to a chair, and
progressing to tasks such as walking short and long distances and
climbing stairs. Results using mobility measures have proven
valuable to the study of the relationship between functional
status and demographic characteristics and chronic conditions,
health-related behaviors, changes in weight, and
osteoarthritis.5

The questions asked were the following: "Usually, due to health problems,
do you have difficulties in: 1) eating, showering, or using the toilet?; 2)
running, lifting heavy loads, practicing sports, or performing heavy work?;
3) pushing a table or doing housework?; 4) climbing stairs?; 5) crouching or
kneeling?; 6) walking more than one kilometer?; 7) walking about 100 meters?".
Answers included the categories 'unable,'with great difficulty,' 'with
some difficulty,' and 'without difficulty.'

Mobility disability is not an attribute clearly present or
absent, but is a matter of degree. Although policy makers tend to
classify people as with or without a given disability, there is
actually a full spectrum of limitations, ranging from mild to
extremely severe.

Considering functional disability as a progressive process, we used a scale
of mobility disability including three measures: a) difficulty eating, showering,
and using the toilet  the basic ADL measure, used as a measure of 'severe mobility
disability' in the scale proposed; b) difficulty walking more than 100 meters  a measure of moderate limitation, used as a good prognostic marker for the
failure process in elderly persons; and c) difficulty walking more than one
kilometer  used as a measure of mild mobility disability. These three measures
were selected because their significance to the evaluation of normal behavior
is clear, they are relatively and culturally independent, and they have been
used previously as indicators of disability.

Sociodemographic variables included sex, age, skin color,
place of residence, urban/rural residence, schooling, family
income, family composition, family and residence size, home
ownership and sanitary conditions, and ownership of durable
goods.

Schooling was analyzed in complete years. Monthly family per capita income  expressed in percentiles  was calculated as the total family income in the
month preceding the interview divided by the number of persons in the family.
Two measures were created: sanitary conditions of the home, including lighting;
and ownership of durable goods, including access to refrigerator, telephone,
and washing machine.

Data were processed and analyzed using SPSS-10 software.
Statistical analysis was based on the information from the sample
rather than on data expanded by weighting. This approach was used
because the size and self-representativeness of the sample made
the differences between weighted and non-weighted estimates
inexpressive. Moreover, comparisons between estimates obtained
using the non-weighted sample and estimates based on information
from the 2000 Demographic Census confirm representativeness of
the former by sex and age.

Logistic regression was used for constructing two models,
with difficulty walking 100 meters as the dependent
variable.

The choice of this indicator of moderate mobility disability
for use as a dependent variable in the logistic regression
analysis is due to the following reasons:

Recent studies indicate that measures of physical mobility, especially those
related to medium distances, are a good prognostic marker of the process of
failure in elderly persons, whereas measures of ADL are an indicator of a
very advanced stage of the process, little useful when dealing with prevention
and intervention, and measures of mild mobility disability are more adequate
for the evaluation of patterns of active aging;11

The logistic regression models used, which consider measures of mild and severe
mobility disability as the dependent variable, did not differ substantially
from the model employing a measure of moderate difficulty.

RESULTS

In 1998, there
were approximately 14 million people aged 60 years or older in Brazil, representing
roughly 9% of the country's total population. Table
1 presents the distribution of sociodemographic variables in the sample.

Differences in terms of sex and age are important when
describing the elderly population of Brazil. As observed
worldwide, the number of elderly women in Brazil is greater than
that of elderly men, and the information from the PNAD show that,
in 1998, 44.1% of the country's elderly population were men and
55.9% were women.

As seen in Table
1, as is the case with the general population, elderly women live mostly
in the country's two largest regions  the Southeast and Northeast  and are
concentrated in the urban areas. Schooling is extremely low: 41.9% of elderly
women are illiterate and only 13.8% have eight or more years of schooling. Elderly
women consistently report lower schooling than men.

Median family income was about R$166.00 per capita. As the distribution of
income in Brazil is highly concentrated, even within the highest quartile of
income  in which median per capita income is R$770.00*  there is great inequality.

Elderly women live with their families, with children
(48,8%), or as couples (23.9%). However, 14.8% live alone, a
higher proportion than of men in the same situation
(8.1%).

Figure shows the prevalence of functional disability among
elderly women according to type of limitation. The most frequent limitations
are those that require greater physical effort, such as climbing stairs or walking
more than one kilometre. It should be noted, however, that many elderly women
do not report difficulty in performing even such demanding activities. Thus,
even among the 85+ years age group, 14.1% of women (95%CI: 11.6-16.5) did not
report difficulty in walking more than one kilometre. Difficulty with basic
activities such as eating, using the toilet, and showering were less frequent,
affecting 17.1% of women (95%CI: 15.7-18.5).

Table 2 presents the prevalence of mobility
disability among elderly women in Brazil according to these types of limitations  severe, moderate, or mild  and selected sociodemographic indicators. According
to these indicators, distribution is relatively uniform within each of the three
levels of mobility disability, despite the differences in magnitude between
them. Family income, schooling, and goods ownership showed the greatest differences
in terms of the prevalence of mobility disability among elderly women.

Table 3 presents the odds ratios (OR) for mobility
disability according to each of the studied variables, showing first univariate
associations adjusted for age, followed by multivariate probabilities adjusted
for all other variables.

The estimated univariate associations show that, after
adjustment for age, the following factors were associated with
moderate mobility disability: skin color, sanitary conditions
in the household, schooling, house size, urban/rural residence,
family income, and goods ownership.

After adjustment for all variables (presented in Table
3), increases in age, reported white skin color, ownership of
a greater number of durable consumption goods, and lower levels of income
and schooling showed the strongest associations with increased risk of mobility
disability. Living in urban areas, when compared to rural areas, was
also a significant risk factor for mobility disability among women.

DISCUSSION

The present study shows that the pattern of mobility
disability among Brazilian women is similar to those found in
other countries. It also suggests that aging is not synonymous
with mobility disability, since even in the 85+ years age group
many women did not report difficulty in walking more than one
kilometre.

Brazil is a country with great diversity, including regional
differences, racial diversity, and differences in family and
household composition. We expected these factors to be associated
with mobility disability; however, the present study showed that
material circumstances and schooling are the dominant factors in
the differences in mobility disability found among these
women.

White skin color and urban residence also appeared as
associated risk factors. According to several
authors,13,14 adjustment for socioeconomic indicators
of associations between skin color and healthcare-related
outcomes must be used cautiously, since such indicators are part
of the causal mechanisms lying in between skin color and the
outcome. Further studies regarding the differences found between
urban and rural areas are required, since the association found
may indicate different lifestyles in these areas or
under-reporting of mobility disability by rural
residents.

When evaluating the results of the present study, we must
also consider the limitations of our data. Firstly, the rural
sample is incomplete, since it does not include the rural area of
the North Region due to the logistic complexity of data
collection in this region. Furthermore, our questions regarding
disability comprised mainly physical function, and we were not
able to use any measures of cognitive disability or mental
health. Thus, such factors are reflected in the results only if
they are severe enough so as to affect the functional aspects
assessed in the survey.

Ideally, analyses of the distribution of mobility disability should include
complementary data on known risk factors such as smoking, alcohol consumption,
and physical exercise. Additionally, more reliable information on the occurrence
of diseases would be useful in order to better understand the pathologies and
lesions that lead to the development of functional limitations. Unfortunately,
no behavioral data is available and the information we have on disease is self-reported  and therefore probably of limited accuracy, given the low level of schooling
of the elderly population and the difficulties in access to the public healthcare
system in Brazil.

When studying socio-economic differences in relation to
mobility disability, it is important that the issues raised have
the same meaning across the different social groups, and that
precise information be obtained. For instance, the question on
"difficulty eating, using the toilet, or showering" may introduce
an information bias due to differences in the accessibility of
sanitary installations between the different groups. Therefore,
it could also not be used as an outcome measure in the regression
models.

On
the other hand, reported family income proved to be an adequate
measure for dividing the elderly population into five broad
income groups, although there is also a potential information
bias related to the rounding of income values close to the
minimum wage in September 1998. Furthermore, the extreme income
concentration seen in Brazil has hindered the measurement of the
risk of mobility disability among groups located below the median
income level. This occurred because family incomes were low and
homogeneous, making it difficult to discriminate between these
subjects in terms of differences in the risk of mobility
disability.

Even though our data show certain limitations, they are also
quite robust. This is due to the large sample size and to its
nationwide coverage. In fact, the survey conducted (PNAD)
provides the first set of information on functional disability at
the national level. Moreover, it includes a broad range of
sociodemographic variables, thus allowing for analyses of the
influence of these variables on functional disability among the
Brazilian elderly. Data on functional disability also provide
information on widely employed indicators, including mobility
indicators, for which these is extensive evidence regarding
validity and predictive value.

Comparisons between these rates and the results obtained in
recent studies from other countries are difficult, since the
questions posed are often different. Furthermore, many studies
from developed countries exclude the institutionalized elderly,
thus removing a high proportion of elderly persons with some type
of functional disability from the overall estimates. A high
proportion of the elderly are institutionalized in these
countries, which is in contrast to the scenario in Brazil, where
institutionalized elderly represent less than 1% of the elderly
population.

One exception is the Health Survey of England 2000,7 which produced
estimates including all persons. Table 4 shows
data on comparable items, and, even though the measures are not exactly identical,
prevalence rates for the ADL measure were very similar. In addition, prevalence
rates for walking 200m (England) or 100 m (Brazil) are also very similar.

The prevalence of difficulty climbing stairs was greater in
Brazil than in England. Two factors may explain this difference:
a) a specific number of steps was not defined in the question
asked in the PNAD; b) in Brazil, climbing stairs may not be a
familiar task for many elderly persons, in contrast to England,
where the presence of stairs in residences is common.

Even considering these limitations and differences, the
results presented may be interpreted as suggestive of potential
risk factors for the development of functional decline in elderly
persons, since they are consistent with the results of other
studies. The characteristics identified as associated with
moderate functional disability integrate the complex causal
network behind functional decline. However, preventive measures
aimed at achieving improvements in these factors may increase the
functionality of the elderly population and, consequently, the
quality of the additional years of life acquired in recent
decades.